Founding MLOps - Data Platform Engineer

Noïa Labs; Paris; Presencial; EUR 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity package

Full health coverage

100% reimbursement of public transport

Meal vouchers

New MacBook Pro

RTT

Descripción de la vacante

Noïa Labs in Paris is seeking a talented MLOps / Data Platform Engineer to build the data and ML infrastructure behind our non-invasive neural interface. You will own systems that ingest, version, and serve large-scale neural data, making model training fast, reproducible, and scalable from dataset construction to deployment.

This hands-on role spans data pipelines, ML workflows, compute infrastructure, experiment tracking, model deployment, and internal tooling, collaborating with ML engineers,

Formación

• 5+ years of experience building production-grade MLOps and data infrastructure.
• Strong software engineering experience, especially in Python.
• Experience with cloud infrastructure, containers, CI/CD, and production systems.
• Experience supporting GPU workloads or distributed training.
• Experience with ML tooling for training, evaluation, tracking, or deployment.
• Strong understanding of data quality, monitoring, versioning, and reproducibility.
• Strong ownership, practical problem-solving skills, and attention to detail.

Responsabilidades

• Build and maintain the platform for neural data ingestion, processing, storage, and retrieval.
• Develop pipelines for dataset generation, training, evaluation, and deployment.
• Create tools that help ML engineers and scientists find data, run experiments, compare models, and reproduce results.
• Manage cloud and GPU compute for scalable ML workloads.
• Improve data quality, metadata, versioning, monitoring, and traceability.
• Work with software and ML teams to integrate models into the platform.
• Help define standards for reliability, reproducibility, privacy, and security.

Conocimientos

Python

MLOps

Data infrastructure

Cloud computing

CI/CD

GPU workloads

Herramientas

AWS

GCP

Docker

Kubernetes

Descripción del empleo

About Noïa Labs

Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces.

We’re tackling one of the most ambitious problems in human-AI interaction: decoding human intent directly from brain signals, in real time and without surgery, to control and collaborate with AI systems.

Our approach combines optimized neural sensors with large-scale AI models trained across many users, a technical challenge that sits at the intersection of neurotechnologies and frontier AI.

Founded by the team behind NextMind (acquired by Snap) and backed by tier-1 investors, Noïa Labs is starting its journey and hiring a team of outstanding engineers and scientists where each person will have a major impact on the product and technology.

Your Mission

We are seeking a talented MLOps / Data Platform Engineer to build the data and ML infrastructure behind our non-invasive neural interface. You will own the systems that ingest, version, and serve large-scale neural data, making model training fast, reproducible, and scalable from dataset construction and orchestration through distributed training and deployment.

This is a hands-on role for someone who enjoys building reliable infrastructure for fast-moving ML and research teams. The role spans data pipelines, ML workflows, compute infrastructure, experiment tracking, model deployment, and internal tooling, while working closely with ML engineers, neuroscientists, software engineers, and product teams.

What you’ll do:

• Build and maintain the platform for neural data ingestion, processing, storage, and retrieval

• Develop pipelines for dataset generation, training, evaluation, and deployment

• Create tools that help ML engineers and scientists find data, run experiments, compare models, and reproduce results

• Manage cloud and GPU compute for scalable ML workloads

• Improve data quality, metadata, versioning, monitoring, and traceability

• Work with software and ML teams to integrate models into the platform

• Help define standards for reliability, reproducibility, privacy, and security

What we are looking for:

• 5+ years of experience building production-grade MLOps and data infrastructure

• Strong software engineering experience, especially in Python

• Experience with cloud infrastructure, containers, CI/CD, and production systems

• Experience supporting GPU workloads or distributed training

• Experience with ML tooling for training, evaluation, tracking, or deployment

• Strong understanding of data quality, monitoring, versioning, and reproducibility

• Strong ownership, practical problem-solving skills, and attention to detail

Nice to have:

• Experience with time-series data such as biosignals, sensor data, audio, video, or robotics

• Experience with real-time streaming, edge buffering, device-to-cloud synchronization, or intermittent connectivity

• Experience in health, medical device, regulated, privacy-sensitive, or research environments

Benefits & Compensation:

• Equity package

• Full health coverage, employer-paid through Alan

• 100% reimbursement of public transport costs (Paris-based)

• Meal vouchers at €11 per working day, 60% company-funded

• New MacBook Pro

• RTT (extra days off)

Even if you don’t check every box in our requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we’re more interested in your potential and passion than a perfect match to our checklist.

In case of any doubts or questions, please contact - [e-mail]